Objective: To investigate potential improvements in signal-to-noise (SNR) derived from advanced image analysis of longitudinal DAT-SPECT data.

Background: [¹²³I]Ioflupane SPECT (DAT-SPECT) has been widely used as an eligibility criteria for numerous PD clinical trials. More recently DAT has emerged as a key anchor for the recently proposed Biologic definition and Integrated Staging Framework for neuronal synuclein disease (NSD-ISS) [1]. Current quantitative DAT analysis has been utilized to establish cut-offs for NSD stage. In addition, change in DAT has been proposed as a key outcome in the planned Path to Prevention (P2P) study. Optimizing the quantification of DAT would enable more accurate identification of early neurodegeneration and more power to detect change in DAT most particularly in NSD subsets and in response to therapy.

Method: DAT-SPECT imaging data from 41 Parkinson’s Disease subjects from the Parkinson’s Progression Markers Initiative (PPMI) who had a baseline and at least one longitudinal follow up scan were used.

The advanced analytical pipeline developed in MIAKAT^TM included motion correction, frame averaging, spatial normalisation and application of regions of interest in template space. The reference region was chosen to be the cerebral white matter and the target region as the bi-lateral putamen. This enabled calculation of the specific binding ratio (SBR) outcome measure in the putamen.

results were compared with the historical PPMI SBR values that had previously been acquired from an analytical pipeline that used the occipital cortex as the reference region. The results were compared by calculating the SNR derived from the longitudinal data (for both Delta and %Change metrics). This then enabled sample size calculations to be performed for theoretical clinical trials.

Results: The signal-to-noise for the longitudinal data [table1] showed an ~50% increase at 12 m and over 100% increase at 24 m for the advanced pipeline. This translated into a reduction in clinical trial sample size estimates of over 50% at 12 m and over 75% at 24 m [table2].

Conclusion: The proposed analytical pipeline demonstrated a significant increase in signal and reduction in variability for the analysis of DAT-SPECT data. This has Important value for use in future clinical trial as part of biological staging and eligibility along with monitoring of therapeutic interventions.

Longitudinal signal-to-noise.

Sample size estimates.

References: [1] Simuni T, Chahine LM, Poston K, et al. A biological definition of neuronal alpha-synuclein disease: towards an integrated staging system for research. Lancet neurology 2024; 23(2): 178-90.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/improved-quantification-of-dat-spect-significantly-increases-its-performance-as-an-imaging-biomarker-in-parkinsons-disease/